Overview  Introduction  Biological network data  Text mining  Gene Ontology  Expression data basics  Expression, text mining, and GO  Modules and.

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Presentation transcript:

Overview  Introduction  Biological network data  Text mining  Gene Ontology  Expression data basics  Expression, text mining, and GO  Modules and complexes  Domains and conclusion

Biological Network Data (Getting external stuff)  Lecture  Cytoscape plugins  Protein interactions: types and measurement  Protein association: text mining and coexpression  Public data repositories  Hands-on  Installing Cytoscape plugins  Filters  A few external data resources

Cytoscape Plugins available for….  Gene Ontology analysis  Domain-level protein network analysis  Interface to the Oracle spatial network data model  Shortest-Path graph analysis algorithms

Interactions  Protein-protein interactions  Protein-DNA interactions  Associations (co-expression, text mining, etc).

Protein-protein interactions Source:

Measuring protein-protein interactions:  Yeast Two-Hybrid Source:

Measuring protein-protein interactions  Co-immunoprecipitation (Co-IP) Courtesy of Rhoded Sharan, Tel Aviv University

Key points on protein interactions  High false positive rate  High false negative rate  Currently, not much overlap between published interaction datasets  Most confidence given to observed interactions with other supporting evidence.

Protein-DNA interactions From: Molecular Biology of the Cell, Alberts et al., 2002

Measuring Protein-DNA Interactions  ChIP-on-chip From:

Key points on protein-DNA interactions  There has not been much data historically.  With new technology, that is changing rapidly.  The technology is still immature, and data interpretation should be done cautiously.

Text mining Courtesy of Gary Bader, Memorial Sloan Kettering Cancer Center

Conserved co-expression networks From: Genome Biology 2004, 5: R100

Genetic Interactions From: Nature Biotechnology 23, (2005)

Key points on association data  An association does not imply an interaction.  Compared to protein interaction data  Higher false positive rate  Often better coverage, lower false negative rate

From: de Lichtenberg et al., Science Feb 4;307(5710):724-7 Always remember: interactions are context-dependent!

Also: Metabolic pathways

Public data repositories  Protein-protein interaction data  BIND, DIP, MINT, MIPS, InACT, …  Protein-DNA interaction data  BIND, Transfac, …  Metabolic pathway data  BioCyc, KEGG, WIT, …  Text-mining, coexpression  Pre-BIND, Tmm, …

Pathway data exchange formats: 1. BioPAX (supported by Cytoscape) 2. PSI-MI (supported by Cytoscape) 3. Hundreds of other formats specific to each pathway data repository (not generally supported by Cytoscape)

Hands-on session  Installing Cytoscape plugins  Getting external data  Merging networks  Using filters